Fakeddit
Kai Nakamura, Sharon Levy, and William Yang Wang. 2019. Fakeddit: novel large multimodal fine-grained dataset for automatic fake news detection. It's not a subreddit. It's named Fakeddit because Fake News + Reddit = Fakeddit
Paper: _
Our lab: http://nlp.cs.ucsb.edu/index.html
Getting Started
Follow the instructions to download the dataset. You can download text, metadata, comment data, and image data
Note that released test set is public. Private test set is used for leaderboard.
Prerequisites
script tested on python 3.5
Follow the steps here to obtain client_id, client_secret, and user_agent
Installing
Download text, comment, and metadata
$ git clone https://github.com/entitize/Fakeddit.git
Download image data
Install required python libraries
$ pip install -r requirements.txt
Run image downloader
$ python image_downloader.py type client_id client_secret user_agent
substitute type with either train, validate, or test
substitute client_id, client_scret and user_agent with your own values
If you encounter an error, make sure the command line parameters you set don't have any ( or ) or any other funny characters
Usage
train.tsv, validate.tsv, and test.tsv contain text and metadata for the training, validation, and public testing datasets respectively.
comments.tsv consists of comments made by Reddit users on submissions in the entire released dataset. Use the submission_id column to identify which submission the comment is associated with. Note that one submission can have zero, one, or multiple comments.